Prediction of spatio-temporal land use/land cover dynamics in rapidly developing Varanasi district of Uttar Pradesh, India, using geospatial approach: a comparison of hybrid models

Abstract

Land use/land cover changes (LULCC) are one of the foremost aspects of environmental changes caused by human-induced activities mainly in rapidly developing areas. This study endeavors to evaluate and compare three hybrid models: stochastic Markov chain (ST-MC), cellular automata-Markov chain (CA-MC), and multi-layer perceptron-Markov chain (MLP-MC) to predict future land use/land cover (LULC) scenario in Varanasi district. LULC information extracted for years 1988 and 2001 was first employed to predict LULC scenario for 2015 using three hybrid models. The predicted results were compared with the observed LULC information for the year 2015 to appraise the validity of models through kappa index statistics. The MLP-MC model yielded reliable and best results. Finally, based on this consequence, the prediction of future LULC scenarios for years 2030 and 2050 was performed. The findings of this study exhibited the constant but overall increase of built up area and a considerable reduction in agricultural land. The results also demonstrate the potentiality of MLP-MC hybrid model for better understanding of spatio-temporal dynamics and predicting future landsacpe scenario in Varanasi district of Uttar Pradesh, India.